Characterization of Cardiac Fat in Atrial Fibrillation Patients Prior to Ablation Treatment
Bibliographic record
Abstract
Epicardial adipose tissue (EAT) and pericardial adipose tissue (PAT) contribute to the development of left atrial fibrillation (AF). The purpose of this study is to determine the factors influencing cardiac fat, evaluate its impact on heart function, and evaluate its role in the recurrence of AF. Cardiac MRI exams of n = 198 patients with paroxysmal AF were retrospectively analyzed to quantify EAT and PAT. Body mass index (BMI) showed significant associations with increased EAT, PAT, and total cardiac fat, particularly with the total end-systolic area (p < 0.001). Males were associated with increased PAT (r = −0.331, p < 0.001) and EAT (r = −0.168, p = 0.019). Increased PAT end-diastolic volume was also associated with an increase in LV mass (r = 0.249, p < 0.01). An inverse relationship between EAT end-systolic area and cardiac index (r = −0.220, p < 0.01) was observed. Although BMI did not significantly affect AF recurrence, overweight patients (36%) experienced slightly more AF recurrence than obese patients (33%). Obesity is substantially associated with an increase in EAT and PAT, while sex appears to play a greater role in PAT than EAT and decreased cardiac function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".